Scienziato Data Science

We are seeking a talented and motivated Data Scientist to join our team and contribute to the development of data-driven solutions that address real-world business challenges. This role offers the opportunity to work with advanced machine learning models, large datasets, and modern analytics tools in a collaborative, innovation-focused environment. If you have a passion for extracting insights from data, a strong foundation in statistical analysis and machine learning, and a problem-solving mindset, we’d love to hear from you!

Key Responsibilities

• Collect business requirements and translate them into technical solutions and algorithm specifications
• Design, develop, and implement analytics solutions using sound engineering principles and best practices
• Conduct risk analysis, conceptual design reviews, and ensure alignment with product requirements
• Execute software development in incremental cycles with continuous monitoring and validation
• Perform analytics validation at fleet level and manage deployment to production environments
• Ensure compliance with data science standards and conduct quality assurance of solutions
• Coordinate with cross-functional teams and present results to business stakeholders

Required Qualifications

• Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field
• 3+ years of experience in machine learning, statistical modeling, or related analytical roles
• Strong proficiency in Python and solid foundation in machine learning, data analysis, and statistics
• Proficiency with statistical analysis and machine learning fundamentals
• Hands-on experience with software development best practices and version control systems.
• Understanding of SQL and database management systems
• Excellent analytical and problem-solving skills with a high attention to detail

Preferred Qualifications

• Master's degree in Data Science, Statistics, or a related quantitative field
• Experience with advanced machine learning algorithms and ensemble methods
• Hands-on knowledge of data preprocessing techniques and feature engineering
• Familiarity with cloud-based development and deployment environments.
• Understanding of MLOps principles and deployment pipelines.
• Experience with deep learning frameworks (TensorFlow, PyTorch) and neural network architectures
• Understanding of time series analysis and advanced forecasting technique

Apply now to join our innovative team and help shape the future of AI!